Following the work of Ahn et al. Ahn05, the temporal expression extraction task is now conventionally divided into two main steps: identification and normalization. In the former step, the effort is concentrated on how to detect the right boundary of temporal expressions in the text. In the normalization step, the aim is to interpret and represent the temporal meaning of the expressions using TimeML [1]} format. In the TempEval-3 challenge [2]} the normalization task is focused only on two temporal attributes: type and value.
